Lagrangian modeling used for improving ice core interpretation

<p>Atmospheric transport modeling with the Lagrangian Particle Dispersion Model (LPDM) FLEXPART has been used for the interpretation of ice core records in several studies in the recent past. Here we present (1) the methodology and results of a study looking into the historical black carbon (BC) emissions based on inverse modeling of ice core records, (2) discuss preliminary results and further plans for a similar study looking into the historical sulphur dioxide (SO₂) emissions, (3) and give a short overview of other ice core studies using FLEXPART simulations.</p> <p>Both, BC and SO₂ emissions, are caused by anthropogenic as well as natural processes, e.g., (incomplete) combustion of fossil fuels / biomass and volcanic eruptions. And, both negatively influence our health and environment, e.g., causing premature mortality, lowering surface albedo, producing acid rain. However, both species also act as climate forcers, and therefore an accurate knowledge of past BC/SO₂ emissions is essential to quantify and model associated global climate forcing. Nowadays, commonly used bottom-up BC/SO₂ emission inventories for historical Earth System Modeling (ESM), e.g., for the Coupled Model Intercomparison Project Phase 5 / Phase 6 (CMIP5/CMIP6) are poorly constrained by observations prior to the late 20^thcentury.</p> <p>In a recent study, we revisit and evaluate these historical 1850 to 2000 BC emission inventories used for ESM simulations, based on an array of deposition ice core records, Lagrangian atmospheric modeling with the FLEXPART model, and an objective inversion technique in order to bring the spatial-temporal patterns of emission inventories in accordance with observed deposition at the ice core sites. We find substantial discrepancies between our reconstructed BC emissions and the existing bottom-up inventories which do not fully capture the complex spatial-temporal BC emission patterns. Our findings imply changes to existing historical BC radiative forcing estimates are necessary, with potential implications for observation-constrained climate sensitivity.</p>